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from __future__ import annotations
import json
from typing import TYPE_CHECKING, Any, Callable, Sequence
from airflow.exceptions import AirflowException
from airflow.models import BaseOperator
from airflow.providers.apache.hive.hooks.hive import HiveMetastoreHook
from airflow.providers.mysql.hooks.mysql import MySqlHook
from airflow.providers.presto.hooks.presto import PrestoHook
if TYPE_CHECKING:
from airflow.utils.context import Context
[docs]class HiveStatsCollectionOperator(BaseOperator):
"""Gather partition statistics and insert them into MySQL.
Statistics are gathered with a dynamically generated Presto query and
inserted with this format. Stats overwrite themselves if you rerun the
same date/partition.
.. code-block:: sql
CREATE TABLE hive_stats (
ds VARCHAR(16),
table_name VARCHAR(500),
metric VARCHAR(200),
value BIGINT
);
:param metastore_conn_id: Reference to the
:ref:`Hive Metastore connection id <howto/connection:hive_metastore>`.
:param table: the source table, in the format ``database.table_name``. (templated)
:param partition: the source partition. (templated)
:param extra_exprs: dict of expression to run against the table where
keys are metric names and values are Presto compatible expressions
:param excluded_columns: list of columns to exclude, consider
excluding blobs, large json columns, ...
:param assignment_func: a function that receives a column name and
a type, and returns a dict of metric names and an Presto expressions.
If None is returned, the global defaults are applied. If an
empty dictionary is returned, no stats are computed for that
column.
"""
[docs] template_fields: Sequence[str] = ("table", "partition", "ds", "dttm")
def __init__(
self,
*,
table: str,
partition: Any,
extra_exprs: dict[str, Any] | None = None,
excluded_columns: list[str] | None = None,
assignment_func: Callable[[str, str], dict[Any, Any] | None] | None = None,
metastore_conn_id: str = "metastore_default",
presto_conn_id: str = "presto_default",
mysql_conn_id: str = "airflow_db",
ds: str = "{{ ds }}",
dttm: str = "{{ logical_date.isoformat() }}",
**kwargs: Any,
) -> None:
super().__init__(**kwargs)
self.table = table
self.partition = partition
self.extra_exprs = extra_exprs or {}
self.excluded_columns: list[str] = excluded_columns or []
self.metastore_conn_id = metastore_conn_id
self.presto_conn_id = presto_conn_id
self.mysql_conn_id = mysql_conn_id
self.assignment_func = assignment_func
self.ds = ds
self.dttm = dttm
[docs] def get_default_exprs(self, col: str, col_type: str) -> dict[Any, Any]:
"""Get default expressions."""
if col in self.excluded_columns:
return {}
exp = {(col, "non_null"): f"COUNT({col})"}
if col_type in {"double", "int", "bigint", "float"}:
exp[(col, "sum")] = f"SUM({col})"
exp[(col, "min")] = f"MIN({col})"
exp[(col, "max")] = f"MAX({col})"
exp[(col, "avg")] = f"AVG({col})"
elif col_type == "boolean":
exp[(col, "true")] = f"SUM(CASE WHEN {col} THEN 1 ELSE 0 END)"
exp[(col, "false")] = f"SUM(CASE WHEN NOT {col} THEN 1 ELSE 0 END)"
elif col_type == "string":
exp[(col, "len")] = f"SUM(CAST(LENGTH({col}) AS BIGINT))"
exp[(col, "approx_distinct")] = f"APPROX_DISTINCT({col})"
return exp
[docs] def execute(self, context: Context) -> None:
metastore = HiveMetastoreHook(metastore_conn_id=self.metastore_conn_id)
table = metastore.get_table(table_name=self.table)
field_types = {col.name: col.type for col in table.sd.cols}
exprs: Any = {("", "count"): "COUNT(*)"}
for col, col_type in list(field_types.items()):
if self.assignment_func:
assign_exprs = self.assignment_func(col, col_type)
if assign_exprs is None:
assign_exprs = self.get_default_exprs(col, col_type)
else:
assign_exprs = self.get_default_exprs(col, col_type)
exprs.update(assign_exprs)
exprs.update(self.extra_exprs)
exprs_str = ",\n ".join(f"{v} AS {k[0]}__{k[1]}" for k, v in exprs.items())
where_clause_ = [f"{k} = '{v}'" for k, v in self.partition.items()]
where_clause = " AND\n ".join(where_clause_)
sql = f"SELECT {exprs_str} FROM {self.table} WHERE {where_clause};"
presto = PrestoHook(presto_conn_id=self.presto_conn_id)
self.log.info("Executing SQL check: %s", sql)
row = presto.get_first(sql)
self.log.info("Record: %s", row)
if not row:
raise AirflowException("The query returned None")
part_json = json.dumps(self.partition, sort_keys=True)
self.log.info("Deleting rows from previous runs if they exist")
mysql = MySqlHook(self.mysql_conn_id)
sql = f"""
SELECT 1 FROM hive_stats
WHERE
table_name='{self.table}' AND
partition_repr='{part_json}' AND
dttm='{self.dttm}'
LIMIT 1;
"""
if mysql.get_records(sql):
sql = f"""
DELETE FROM hive_stats
WHERE
table_name='{self.table}' AND
partition_repr='{part_json}' AND
dttm='{self.dttm}';
"""
mysql.run(sql)
self.log.info("Pivoting and loading cells into the Airflow db")
rows = [
(self.ds, self.dttm, self.table, part_json) + (r[0][0], r[0][1], r[1]) for r in zip(exprs, row)
]
mysql.insert_rows(
table="hive_stats",
rows=rows,
target_fields=[
"ds",
"dttm",
"table_name",
"partition_repr",
"col",
"metric",
"value",
],
)